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Volumn 1, Issue , 2014, Pages 529-537

Efficient approximation of cross-validation for kernel methods using Bouligand influence function

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS;

EID: 84919816683     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (32)

References (25)
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    • Bouligand derivatives and robustness of support vector machines for regression
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    • Christmann, A.1    Steinwart, I.2
  • 10
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    • On consistency and robustness properties of support vector machines for heavy-tailed distributions
    • Christmann, Andreas, Messem, Arnout Van, and Steinwart, Ingo. On consistency and robustness properties of support vector machines for heavy-tailed distributions. Statistics and Its Interface, 2:311-327, 2009.
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    • Christmann, A.1    Van Messem, A.2    Steinwart, I.3
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    • Model selection in kernel based regression using the influence function
    • Debruyne, Michiel, Hubert, Mia, and Suykens, Johan A.K. Model selection in kernel based regression using the influence function. Journal of Machine Learning Research, 9:2377-2400, 2008.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.